Smart Homes

With the increasing requirements of optical interconnects in high-performance artificial intelligence compute clusters, optical space switches could provide a fast and efficient alternative to existing power-hungry electronic network switches. This work shows the design, fabrication and characterization of the first fully InP monolithically integrated, O-band compatible space switch, using semiconductor optical amplifiers configured in a broadcast-and-select topology. We demonstrate an average fiber-to-fiber insertion loss of 10 dB per optical path and an optical bandwidth of 37 nm. Since no gain saturation is observed, the OSNR is measured up to 47.5 dB. As a result, the transmission experiments show good performance with no distortion and a power penalty below 0.7 dB at 10 Gb/s NRZ, 100 GB/s PAM-4 and using a 100 G LWDM LR4 commercial transceiver with 4 wavelength channels at 25 Gb/s NRZ. We discuss the scalability of the broadcast-and-select topology and demonstrate the viability of an 8 × 8 space switch, which shows comparable results to the 4 × 4 space switch with a negligible power penalty for the majority of the LWDM channels. Based on the results, we discuss the prospects for future designs and highlight potential scalability to larger switches.

External validation of the discriminative ability of prediction models is of key importance. However, the interpretation of such evaluations is challenging, as the ability to discriminate depends on both the sample characteristics (ie, case-mix) and the generalizability of predictor coefficients, but most discrimination indices do not provide any insight into their respective contributions. To disentangle differences in discriminative ability across external validation samples due to a lack of model generalizability from differences in sample characteristics, we propose propensity-weighted measures of discrimination. These weighted metrics, which are derived from propensity scores for sample membership, are standardized for case-mix differences between the model development and validation samples, allowing for a fair comparison of discriminative ability in terms of model characteristics in a target population of interest. We illustrate our methods with the validation of eight prediction models for deep vein thrombosis in 12 external validation data sets and assess our methods in a simulation study. In the illustrative example, propensity score standardization reduced between-study heterogeneity of discrimination, indicating that between-study variability was partially attributable to case-mix. The simulation study showed that only flexible propensity-score methods (allowing for non-linear effects) produced unbiased estimates of model discrimination in the target population, and only when the positivity assumption was met. Propensity score-based standardization may facilitate the interpretation of (heterogeneity in) discriminative ability of a prediction model as observed across multiple studies, and may guide model updating strategies for a particular target population. Careful propensity score modeling with attention for non-linear relations is recommended.

During the first wave of the COVID-19 pandemic, there was a shortage of SARS-CoV-2 diagnostic tests, and testing patients with mild symptoms (low-threshold testing) was not recommended in the Netherlands. Despite these guidelines, to protect those who were most at risk, low-threshold testing was advocated and offered to the majority of long-term care institutions in the Twente region. In this manner, 144 healthcare workers and 96 residents tested SARS-CoV-2-positive and were isolated before the same service was provided nationwide by public health services. Strikingly, excess mortality rate in the Twente region 1 month after the introduction of this strategy was found to be 62%–89% lower than that in neighboring regions, which may be explained by this divergent testing strategy. In an emerging pandemic, early implementation of a liberal testing policy may be more effective than restricted testing in settings with a high death rate.

BACKGROUND During the last few decades, preventing the development of cardiovascular disease has become a mainstay for reducing cardiovascular morbidity and mortality. It has been suggested that interventions should focus more on committed approaches of self-care, such as electronic health techniques. OBJECTIVE This study aimed to provide evidence to understand the financial consequences of implementing the “Do Cardiac Health: Advanced New Generation Ecosystem” (Do CHANGE 2) intervention, which was evaluated in a multisite randomized controlled trial to change the health behavior of patients with cardiovascular disease. METHODS The cost-effectiveness analysis of the Do CHANGE 2 intervention was performed with the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing tool, based on a Markov model of five health states. The following two types of costs were considered for both study groups: (1) health care costs (ie, costs associated with the time spent by health care professionals on service provision, including consultations, and associated unplanned hospitalizations, etc) and (2) societal costs (ie, costs attributed to the time spent by patients and informal caregivers on care activities). RESULTS The Do CHANGE 2 intervention was less costly in Spain (incremental cost was −€2514.90) and more costly in the Netherlands and Taiwan (incremental costs were €1373.59 and €1062.54, respectively). Compared with treatment as usual, the effectiveness of the Do CHANGE 2 program in terms of an increase in quality-adjusted life-year gains was slightly higher in the Netherlands and lower in Spain and Taiwan. CONCLUSIONS In general, we found that the incremental cost-effectiveness ratio strongly varied depending on the country where the intervention was applied. The Do CHANGE 2 intervention showed a positive cost-effectiveness ratio only when implemented in Spain, indicating that it saved financial costs in relation to the effect of the intervention. CLINICALTRIAL ClinicalTrials.gov NCT03178305; https://clinicaltrials.gov/ct2/show/NCT03178305

Baclofen is a new and promising pharmacological compound for the treatment of alcohol dependence (AD). Although several randomised trials found a reduction of craving and higher abstinence rates with low and high doses of baclofen, others failed to show positive effects. In this case study, the successful treatment of a patient with AD with daily 120 mg of baclofen is described. In addition to a decrease in alcohol use, we observed the cessation of stuttering during treatment with baclofen, reoccurrence of stuttering following discontinuation, and cessation of stuttering after reinstatement of the treatment. Based on this observation, the direct effects of baclofen on muscle relaxation and anxiety reduction and its indirect effect on dopaminergic inhibition, we believe that baclofen might be a new treatment for stuttering. Further research into the effect of baclofen on stuttering is warranted.

Discovering older adults’ perceptions and expectations of domestic care service robots are vital in informing the design and development of new technologies to ensure acceptability and usability. This paper identifies issues that were elicited from older adults using different methods to promote creative thinking about domestic robots at an emotional level, as well as pragmatic level. These included exploring people’s ideal embodiment preferences and requirements for a domestic care service robot, and also what embodiments and functional aspects will not be acceptable. We analysed our findings using relevant constructs from the Unified Theory of Acceptance and Use of Technology, and Technology Acceptance models. In addition to some already well-established findings, we discovered some surprising aspects concerning interaction, behaviour and appearance and the ability for the robot to fit the relevant context, both physically and conceptually. Categories and Subject Descriptors Assistive technologies for persons with disabilities, Requirements Elicitation General Terms Design, Human Factors

This paper presents results of the development of a socially assistive home robot companion for older people suffering from mild cognitive impairment (MCI) and living (alone) at home. This work was part of the European FP7 project “CompanionAble” (2008-2012) [1] which aimed at developing assistive technologies that can support these elderly and help them to remain in their familiar living environment for as long as possible. To overcome current market entry barriers, from the start we consistently adopted a user- and application-centered development process of the companion robot and focused on three main aspects: (i) the realization of a set of mandatory functionalities to support care recipients and caregivers, (ii) a strict design and usability driven realization to increase the acceptance of the robot by the different end-user groups (the elderly, their relatives, and caregivers), and (iii) the development and component selection considering production and operational costs. In continuation of the work presented in [2], this paper describes the final implementation of the companion robot and presents latest results of functional tests and early findings of user studies recently conducted in the smart house of the Dutch project partner Smart Homes in Eindhoven, The Netherlands.

Learning digital games can influence both older adults' health condition and their capacity to carry on activities in their actual environment. The goal of the current study was to explore and define the user requirements for developing digital learning games for older Europeans, focusing on types of learning games, motivational and social aspects, and preferences on game controllers. For this initial stage, a qualitative focus group study was performed in three participating countries (Spain, The Netherlands, and Greece) where both games existing in the market and others developed in other European Commission projects like HERMES were presented to them, both on video presentations and also with the possibility to actually test some of them. Challenge, socialization, fun, providing learning opportunities, and escape from daily routine were extracted as the main keys why older people would be interested in playing digital games. Users described themselves as active and participating in many leisure activities, and this level of activity appeared to be related with the contents proposed for digital games, such as physical activity, culture, arts, and other human sciences (history, geography, traveling, foreign languages, music), and daily life skills (cooking, computer use, first aid). The knowledge gathered from the focus groups will be used as input for the design of a learning game that will be largely compatible with the needs and abilities of a wide range of older Europeans.